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2 changes: 1 addition & 1 deletion LICENSE
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MIT License

Copyright (c) 2020 Vijay Prakash Dwivedi, Chaitanya K. Joshi, Thomas Laurent, Yoshua Bengio, Xavier Bresson
Copyright (c) 2022 Vijay Prakash Dwivedi, Chaitanya K. Joshi, Anh Tuan Luu, Thomas Laurent, Yoshua Bengio, Xavier Bresson

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
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## Updates

**Nov 2, 2020**
* Project based on DGL 0.5.2. See the relevant dependencies defined in the environment yml files ([CPU](./environment_cpu.yml), [GPU](./environment_gpu.yml)).
+ Numerical experiments report faster training times with DGL 0.4.2 compared to DGL 0.5.2.
+ For the version of the project compatible with DGL 0.4.2 and relevant dependencies, please use the [master branch](https://github.com/graphdeeplearning/benchmarking-gnns/tree/master).
**May 10, 2022**
* Project based on DGL 0.6.2 and higher. See the relevant dependencies defined in the environment yml files ([CPU](./environment_cpu.yml), [GPU](./environment_gpu.yml)).
* Updated technical report of the framework on [ArXiv](https://arxiv.org/pdf/2003.00982.pdf)
* Added AQSOL dataset, which is similar to ZINC for graph regression task, but has a real-world measured chemical target.
* Added mathematical datasets -- GraphTheoryProp and CYCLES which are useful to test GNNs on specific theoretical graph properties.
* Fixed [issue #57](https://github.com/graphdeeplearning/benchmarking-gnns/issues/57).

**Oct 7, 2020**
* Repo updated to DGL 0.5.2 and PyTorch 1.6.0. Please update your environment using yml files ([CPU](./environment_cpu.yml), [GPU](./environment_gpu.yml)).
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## 7. Leaderboards

[Leaderboards](./docs/07_leaderboards.md) of GNN models on each dataset. [Instructions](./docs/07_contribute_leaderboards.md) to contribute to leaderboards.
Full leaderboards coming soon on [paperswithcode.com](https://paperswithcode.com/paper/benchmarking-graph-neural-networks).


<br>
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```
@article{dwivedi2020benchmarkgnns,
title={Benchmarking Graph Neural Networks},
author={Dwivedi, Vijay Prakash and Joshi, Chaitanya K and Laurent, Thomas and Bengio, Yoshua and Bresson, Xavier},
author={Dwivedi, Vijay Prakash and Joshi, Chaitanya K and Luu, Anh Tuan and Laurent, Thomas and Bengio, Yoshua and Bresson, Xavier},
journal={arXiv preprint arXiv:2003.00982},
year={2020}
}
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"batch_size": 25,
"init_lr": 1e-4,
"lr_reduce_factor": 0.5,
"lr_schedule_patience": 5,
"lr_schedule_patience": 10,
"min_lr": 1e-6,
"weight_decay": 0.0,
"print_epoch_interval": 5,
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"batch_size": 25,
"init_lr": 1e-4,
"lr_reduce_factor": 0.5,
"lr_schedule_patience": 5,
"lr_schedule_patience": 10,
"min_lr": 1e-6,
"weight_decay": 0.0,
"print_epoch_interval": 5,
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"batch_size": 25,
"init_lr": 1e-4,
"lr_reduce_factor": 0.5,
"lr_schedule_patience": 5,
"lr_schedule_patience": 10,
"min_lr": 1e-6,
"weight_decay": 0.0,
"print_epoch_interval": 5,
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"batch_size": 25,
"init_lr": 1e-4,
"lr_reduce_factor": 0.5,
"lr_schedule_patience": 15,
"lr_schedule_patience": 10,
"min_lr": 1e-6,
"weight_decay": 0.0,
"print_epoch_interval": 5,
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36 changes: 36 additions & 0 deletions configs/WikiCS_node_classification_GAT_100k.json
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{
"gpu": {
"use": true,
"id": 0
},

"model": "GAT",
"dataset": "WikiCS",

"out_dir": "out/WikiCS_node_classification/",

"params": {
"seed": 41,
"epochs": 1000,
"init_lr": 1e-2,
"lr_reduce_factor": 0.5,
"lr_schedule_patience": 25,
"min_lr": 1e-5,
"weight_decay": 5e-4,
"print_epoch_interval": 5,
"max_time": 24
},

"net_params": {
"L": 4,
"n_heads": 8,
"hidden_dim": 15,
"out_dim": 120,
"residual": true,
"readout": "mean",
"in_feat_dropout": 0.0,
"dropout": 0.35,
"batch_norm": true,
"self_loop": false
}
}
35 changes: 35 additions & 0 deletions configs/WikiCS_node_classification_GCN_100k.json
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{
"gpu": {
"use": true,
"id": 0
},

"model": "GCN",
"dataset": "WikiCS",

"out_dir": "out/WikiCS_node_classification/",

"params": {
"seed": 41,
"epochs": 1000,
"init_lr": 1e-2,
"lr_reduce_factor": 0.5,
"lr_schedule_patience": 25,
"min_lr": 1e-5,
"weight_decay": 5e-4,
"print_epoch_interval": 5,
"max_time": 24
},

"net_params": {
"L": 4,
"hidden_dim": 120,
"out_dim": 120,
"residual": true,
"readout": "mean",
"in_feat_dropout": 0.0,
"dropout": 0.35,
"batch_norm": true,
"self_loop": false
}
}
36 changes: 36 additions & 0 deletions configs/WikiCS_node_classification_GIN_100k.json
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{
"gpu": {
"use": true,
"id": 0
},

"model": "GIN",
"dataset": "WikiCS",

"out_dir": "out/WikiCS_node_classification/",

"params": {
"seed": 41,
"epochs": 1000,
"init_lr": 1e-2,
"lr_reduce_factor": 0.5,
"lr_schedule_patience": 25,
"min_lr": 1e-5,
"weight_decay": 5e-4,
"print_epoch_interval": 5,
"max_time": 24
},

"net_params": {
"L": 4,
"hidden_dim": 96,
"residual": true,
"readout": "sum",
"n_mlp_GIN": 2,
"learn_eps_GIN": true,
"neighbor_aggr_GIN": "sum",
"in_feat_dropout": 0.0,
"dropout": 0.35,
"batch_norm": true
}
}
36 changes: 36 additions & 0 deletions configs/WikiCS_node_classification_GatedGCN.json
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{
"gpu": {
"use": true,
"id": 0
},

"model": "GatedGCN",
"dataset": "WikiCS",

"out_dir": "out/WikiCS_node_classification/",

"params": {
"seed": 41,
"epochs": 1000,
"init_lr": 1e-2,
"lr_reduce_factor": 0.5,
"lr_schedule_patience": 25,
"min_lr": 1e-5,
"weight_decay": 5e-4,
"print_epoch_interval": 5,
"max_time": 24
},

"net_params": {
"L": 4,
"hidden_dim": 65,
"out_dim": 65,
"residual": true,
"readout": "mean",
"in_feat_dropout": 0.0,
"dropout": 0.35,
"batch_norm": true,
"self_loop": false,
"pos_enc": false
}
}
35 changes: 35 additions & 0 deletions configs/WikiCS_node_classification_GraphSage_100k.json
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{
"gpu": {
"use": true,
"id": 0
},

"model": "GraphSage",
"dataset": "WikiCS",

"out_dir": "out/WikiCS_node_classification/",

"params": {
"seed": 41,
"epochs": 1000,
"init_lr": 1e-2,
"lr_reduce_factor": 0.5,
"lr_schedule_patience": 25,
"min_lr": 1e-5,
"weight_decay": 5e-4,
"print_epoch_interval": 5,
"max_time": 24
},

"net_params": {
"L": 4,
"hidden_dim": 78,
"out_dim": 78,
"residual": true,
"readout": "mean",
"in_feat_dropout": 0.0,
"dropout": 0.35,
"batch_norm": true,
"sage_aggregator": "maxpool"
}
}
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{
"gpu": {
"use": true,
"id": 0
},

"model": "MLP",
"dataset": "WikiCS",

"out_dir": "out/WikiCS_node_classification/",

"params": {
"seed": 41,
"epochs": 1000,
"init_lr": 1e-2,
"lr_reduce_factor": 0.5,
"lr_schedule_patience": 25,
"min_lr": 1e-5,
"weight_decay": 5e-4,
"print_epoch_interval": 5,
"max_time": 24
},

"net_params": {
"L": 4,
"hidden_dim": 125,
"out_dim": 125,
"readout": "mean",
"gated": false,
"in_feat_dropout": 0.0,
"dropout": 0.35
}
}
37 changes: 37 additions & 0 deletions configs/WikiCS_node_classification_MoNet_100k.json
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{
"gpu": {
"use": true,
"id": 0
},

"model": "MoNet",
"dataset": "WikiCS",

"out_dir": "out/WikiCS_node_classification/",

"params": {
"seed": 41,
"epochs": 1000,
"init_lr": 1e-2,
"lr_reduce_factor": 0.5,
"lr_schedule_patience": 25,
"min_lr": 1e-5,
"weight_decay": 5e-4,
"print_epoch_interval": 5,
"max_time": 24
},

"net_params": {
"L": 4,
"hidden_dim": 80,
"out_dim": 80,
"residual": true,
"readout": "mean",
"kernel": 3,
"pseudo_dim_MoNet": 2,
"in_feat_dropout": 0.0,
"dropout": 0.35,
"batch_norm": true,
"pos_enc": false
}
}
38 changes: 38 additions & 0 deletions configs/WikiCS_node_classification_MoNet_PE_100k.json
Original file line number Diff line number Diff line change
@@ -0,0 +1,38 @@
{
"gpu": {
"use": true,
"id": 0
},

"model": "MoNet",
"dataset": "WikiCS",

"out_dir": "out/WikiCS_node_classification_PE/",

"params": {
"seed": 41,
"epochs": 1000,
"init_lr": 1e-2,
"lr_reduce_factor": 0.5,
"lr_schedule_patience": 25,
"min_lr": 1e-5,
"weight_decay": 5e-4,
"print_epoch_interval": 5,
"max_time": 24
},

"net_params": {
"L": 4,
"hidden_dim": 80,
"out_dim": 80,
"residual": true,
"readout": "mean",
"kernel": 3,
"pseudo_dim_MoNet": 2,
"in_feat_dropout": 0.0,
"dropout": 0.35,
"batch_norm": true,
"pos_enc": true,
"pos_enc_dim": 20
}
}
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